The First Rule: Don’t Lose Money

Markets will eventually move against you. The question is: when that happens, how much do you lose?

Risk management is what keeps you in the game long enough for your edge to play out.

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Core Concepts

Term	Definition
Risk	Probability × Impact of loss
Position size	Amount invested in a trade
Stop loss	Price level to exit losing trade
Drawdown	Peak-to-trough decline
VaR	Value at Risk-max expected loss

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Position Sizing

How much capital to risk on each trade?

Fixed Fractional

Risk a fixed percentage of capital:

Capital: $100,000
Risk per trade: 1%
Risk amount: $1,000

Stock at $50, stop loss at $45
Risk per share: $5
Position size: $1,000 / $5 = 200 shares

Kelly Criterion

Mathematically optimal (but aggressive):

Kelly % = (Win probability × Average win / Average loss - Lose probability) / (Average win / Average loss)

Example:
Win rate: 55%
Average win: $1,000
Average loss: $800

Kelly = (0.55 × 1.25 - 0.45) / 1.25 = 19%

Use half-Kelly (9.5%) in practice-full Kelly is too aggressive

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Stop Losses

Automatic exit when trade goes wrong.

Types

Type	Trigger
Fixed	Price reaches specific level
Trailing	Follows price up, exits on reversal
Volatility	Based on ATR (Average True Range)
Time-based	Exit after X time regardless

Setting Stop Levels

Based on volatility (ATR):
ATR = 2% daily
Stop = 2 × ATR = 4%

Based on support:
Entry at $100
Support at $95
Stop at $94 (below support)

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Risk Limits

Per-Trade Limits

• Max position size: Never more than X% of capital
• Max loss per trade: 1-2% of capital

Daily Limits

Daily loss limit: 5% of capital
Once hit → Stop trading for the day

Why: Prevents emotional revenge trading

Portfolio Limits

• Max correlation exposure: Don’t have all positions in same sector
• Max total risk: Total VaR under threshold
• Leverage limit: Max 2-5x depending on strategy

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Risk Metrics

Drawdown

Peak: $1,000,000
Current: $850,000
Drawdown: ($1,000,000 - $850,000) / $1,000,000 = 15%

Max drawdown is the largest historical peak-to-trough.

Sharpe Ratio

Sharpe = (Return - Risk-free rate) / Standard deviation

Example:
Annual return: 20%
Risk-free rate: 5%
Volatility: 15%

Sharpe = (20% - 5%) / 15% = 1.0

Sharpe	Interpretation
< 1.0	Suboptimal
1.0-2.0	Good
> 2.0	Excellent
> 3.0	Exceptional (suspicious)

Value at Risk (VaR)

95% VaR: Max loss in 95% of days

If 95% VaR = $10,000
→ On 95% of days, you won't lose more than $10,000
→ On 5% of days (1 in 20), you might lose more

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Implementing Risk Controls

Pre-Trade Checks

def can_trade(order, portfolio):
    # Check position limit
    if order.value > portfolio.max_position:
        return False, "Exceeds position limit"
    
    # Check daily loss
    if portfolio.daily_pnl < -portfolio.daily_limit:
        return False, "Daily loss limit reached"
    
    # Check concentration
    if portfolio.exposure(order.sector) > portfolio.sector_limit:
        return False, "Sector concentration limit"
    
    return True, "OK"

Real-Time Monitoring

def monitor_risk(portfolio):
    metrics = {
        'pnl': portfolio.pnl(),
        'drawdown': portfolio.drawdown(),
        'var': portfolio.var_95(),
        'exposure': portfolio.gross_exposure()
    }
    
    for name, value in metrics.items():
        if value > limits[name]:
            alert(f"{name} breach: {value}")

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Practice Exercises

Exercise 1: Position Sizing (Beginner)

Capital: $50,000 Max risk per trade: 2Entry:$100 Stop loss: $95

Calculate position size.

Answer

Risk amount: $50,000 × 2$1,000 Risk per share: $100 -$95 = $5 Position size:$1,000 / $5 = 200 shares

Exercise 2: Risk Metrics (Intermediate)

A portfolio had these monthly returns: +5%, +3%, -2%, +4%, -5%, +2%

Calculate:

1. Total return
2. Max drawdown (within months)

Answer

1. Total: 1.05 × 1.03 × 0.98 × 1.04 × 0.95 × 1.02 = 1.0694 = 6.94%
2. Max drawdown: In month 5 (−5%), from previous peak = 5%

Exercise 3: Design (Advanced)

Design a risk management system for an automated trading strategy with:

• Position limits
• Daily loss limits
• Correlation checks
• Automatic shutdown

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Knowledge Check

1. Why is position sizing important?

2. What is the Kelly Criterion?

3. Why use daily loss limits?

4. What does Sharpe ratio measure?

5. What is Value at Risk (VaR)?

Answers

1. Determines how much you lose when wrong. Too large = one bad trade wipes you out.

2. Formula for optimal bet size based on win rate and win/loss ratio. Often halved due to uncertainty.

3. Prevents revenge trading. After losses, judgment impaired. Limits force a break.

4. Risk-adjusted returns. Return per unit of volatility. Higher = better risk/reward.

5. Maximum expected loss at confidence level. 95% VaR of $10K = won't lose more than$10K on 95% of days.

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Summary

Control	Purpose
Position sizing	Limit loss per trade
Stop losses	Automatic exit
Daily limits	Prevent tilt
Portfolio limits	Diversification
Monitoring	Real-time alerting

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What’s Next?

🎯 Continue learning:

• HFT Basics - Risk in high-speed trading
• Order Book Basics - Market mechanics

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You now understand how professionals protect their capital. 💼